Update README.md

README.md

@@ -136,9 +136,6 @@ The documents are retained in their original file formats without parsing or seg
 
 ### Dataset Description
 
-<!-- Provide a longer summary of what this dataset is. -->
-
-
 
 - **Curated by:** Yulong Hui, Tsinghua University
 - **Language(s) (NLP):** English
@@ -166,7 +163,20 @@ Assess the effectiveness of parsing strategies on unstructured PDF documents.
 ## Dataset Structure
 
 <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
+#### Descriptive Statistics
+
+ Sub Dataset (folder_name) | Source Domain | Doc Format | Doc Num | Q&A Num | Avg #Words | Avg #Pages |Q&A Types 
+ --- | --- | --- | --- | --- | ---| --- |--- 
+FinHybrid (fin) | finance reports  | PDF        | 788 | 8190 | 76.6k | 147.8 |arithmetic
+TatHybrid (tat)|  finance reports |PDF|170|14703|77.5k|148.5|extractive, counting, arithmetic
+PaperTab (paper_tab)| academic papers    |PDF|307|393|6.1k|11.0|extractive, yes/no, free-form 
+PaperText (paper_text)| academic   papers     | PDF|1087|2804|5.9k|10.6|extractive, yes/no, free-form 
+FetaTab (feta)| wikipedia     |PDF & HTML|878|1023|6.0k|14.9|free-form 
+NqText (nq)| wikipedia      |PDF & HTML|645|2477|6.1k|14.9|extractive      
+
+
 
+#### Data Fields
 Field Name | Field Value | Description| Example 
 --- | --- | ---|--- 
 doc_name | string | name of the source document | 1912.01214 
@@ -174,7 +184,7 @@ q_uid | string      | unique id of the question | 9a05a5f4351db75da371f7ac12eb0b
 question | string | raised question | which datasets did they experiment with? 
 answer  <br />or  answer_1, answer_2 <br />or short_answer,  long_answer | string | ground truth answer/answers | Europarl, MultiUN 
 
-**Additional Notes:** Some sub-datasets may have multiple ground_truth answers, where the answers are organized as `answer_1`, `answer_2` (in fin,  paper_tab and paper_text) or `short_answer`, `long_answer` (in nq); In sub-dataset tat, the answer is organized as a sequence, due to the  involvement of the multi-span Q&A type.
+**Additional Notes:**  Some sub-datasets may have multiple ground_truth answers, where the answers are organized as `answer_1`, `answer_2` (in FinHybrid, PaperTab and PaperText) or `short_answer`, `long_answer` (in NqText); In sub-dataset TatHybrid, the answer is organized as a sequence, due to the involvement of the multi-span Q&A type. Additionally, some sub-datasets may have unique data fields. For example, `doc_url` in FetaTab and NqText describes the Wikipedia URL page, while `answer_type` and `answer_scale` in TatHybrid provide extended answer references.
 
 
 ## Dataset Creation